A supervisory-based collaborative Obstacle-Guided Path Refinement algorithm for path planning in wide terrains

Atia, MGB; Hussien, HEHA; Salah, O

Abstract

Robotic exploration of wide terrains, such as agricultural fields, could be challenging while considering the limited robot’s capabilities in terms of sensing and power. Thus, in this article, we proposed OGPR*, an Obstacle Guided Path Refinement algorithm for quickly planning collision-free paths utilizing the obstacles existing in the environment. To tackle the issue of exploring wide terrains, a supervisory-based collaboration between the quadcopter and a mobile robot is proposed. The quadcopter is responsible for streaming subsequently live two-dimensional images for the environment under discussion while planning safe paths for the ground the mobile robot is planning safe paths to manoeuvre. Numerical simulations proved the significant performance of the proposed OGBR* algorithm when compared to the state of the art algorithms exist in the literature.

Citation

Atia, M., Hussien, H., & Salah, O. (2020). A supervisory-based collaborative Obstacle-Guided Path Refinement algorithm for path planning in wide terrains. IEEE Access, 8, 214672-214684. https://doi.org/10.1109/ACCESS.2020.3041802

• Journal Article Type: Article
• Acceptance Date: Nov 26, 2020
• Online Publication Date: Dec 1, 2020
• Publication Date: Dec 10, 2020
• Deposit Date: Jan 7, 2021
• Publicly Available Date: Jan 7, 2021
• Journal: IEEE Access
• Publisher: Institute of Electrical and Electronics Engineers
• Volume: 8
• Pages: 214672-214684
• DOI: https://doi.org/10.1109/ACCESS.2020.3041802
• Publisher URL: https://doi.org/10.1109/ACCESS.2020.3041802
• Related Public URLs: https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639